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(Abridged) The main purpose of this paper is to consider the contribution of all three non-thermal components to total mass measurements of galaxy clusters: cosmic rays, turbulence and magnetic pressures. To estimate the thermal pressure we used public XMM-textit{Newton} archival data of 5 Abell clusters. To describe the magnetic pressure, we assume a radial distribution for the magnetic field, $B(r) propto rho_{g}^{alpha}$, to seek generality we assume $alpha$ within the range of 0.5 to 0.9, as indicated by observations and numerical simulations. For the turbulent component, we assumed an isotropic pressure, $P_{rm turb} = {1/3}rho_{rm g}(sigma_{r}^{2}+sigma_{t}^{2})$. We also consider the contribution of cosmic ray pressure, $P_{cr}propto r^{-0.5}$. It follows that a consistent description for the non-thermal component could yield variation in mass estimates that vary from 10% up to $sim$30%. We verified that in the inner parts of cool-core clusters the cosmic ray component is comparable to the magnetic pressure, while in non cool-core cluster the cosmic ray component is dominant. For cool-core clusters the magnetic pressure is the dominant component, contributing with more than 50% of total mass variation due to non-thermal pressure components. However, for non cool-core clusters, the major influence comes from the cosmic ray pressure that accounts with more than 80% of total mass variation due to non-thermal pressure effects. For our sample, the maximum influence of the turbulent component to total mass variation can be almost 20%. We show that this analysis can be regarded as a starting point for a more detailed and refined exploration of the influence of non-thermal pressure in the intra-cluster medium (ICM).
A recent stacking analysis of Planck HFI data of galaxy clusters (Hurier 2016) allowed to derive the cluster temperatures by using the relativistic corrections to the Sunyaev-Zeldovich effect (SZE). However, the temperatures of high-temperature clust
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The relevance of non-thermal cluster studies and the importance of combining observations of future radio surveys with WFXT data are discussed in this paper.
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